Does your Machine Learning pipeline have a pulse?

The process of building and training Machine Learning models is always in the spotlight. There is a lot of talk about different Neural Network architectures, or new frameworks, facilitating the idea-to-implementation transition. While these are the heart of an ML engine, the circulatory system, which enables nutrients to move around and connects everything, is often missing. But what comprises this system? What gives the pipeline its pulse? The most important component in an ML pipeline works silently in the background and provides the glue that binds everything together.